# encoding: UTF-8 """ R-Breaker交易策略 """ from datetime import time from ctaBase import * from ctaTemplate import CtaTemplate ######################################################################## class DualThrustStrategy(CtaTemplate): """DualThrust交易策略""" className = 'DualThrustStrategy' author = u'用Python的交易员' # 策略参数 fixedSize = 100 k1 = 0.4 k2 = 0.6 initDays = 10 # 策略变量 bar = None # K线对象 barMinute = EMPTY_STRING # K线当前的分钟 barList = [] # K线对象的列表 dayOpen = 0 dayHigh = 0 dayLow = 0 range = 0 longEntry = 0 shortEntry = 0 exitTime = time(hour=14, minute=55) longEntered = False shortEntered = False orderList = [] # 保存委托代码的列表 # 参数列表，保存了参数的名称 paramList = ['name', 'className', 'author', 'vtSymbol', 'k1', 'k2'] # 变量列表，保存了变量的名称 varList = ['inited', 'trading', 'pos', 'range', 'longEntry', 'shortEntry', 'exitTime'] #---------------------------------------------------------------------- def __init__(self, ctaEngine, setting): """Constructor""" super(DualThrustStrategy, self).__init__(ctaEngine, setting) self.barList = [] #---------------------------------------------------------------------- def onInit(self): """初始化策略（必须由用户继承实现）""" self.writeCtaLog(u'%s策略初始化' %self.name) # 载入历史数据，并采用回放计算的方式初始化策略数值 initData = self.loadBar(self.initDays) for bar in initData: self.onBar(bar) self.putEvent() #---------------------------------------------------------------------- def onStart(self): """启动策略（必须由用户继承实现）""" self.writeCtaLog(u'%s策略启动' %self.name) self.putEvent() #---------------------------------------------------------------------- def onStop(self): """停止策略（必须由用户继承实现）""" self.writeCtaLog(u'%s策略停止' %self.name) self.putEvent() #---------------------------------------------------------------------- def onTick(self, tick): """收到行情TICK推送（必须由用户继承实现）""" # 计算K线 tickMinute = tick.datetime.minute if tickMinute != self.barMinute: if self.bar: self.onBar(self.bar) bar = CtaBarData() bar.vtSymbol = tick.vtSymbol bar.symbol = tick.symbol bar.exchange = tick.exchange bar.open = tick.lastPrice bar.high = tick.lastPrice bar.low = tick.lastPrice bar.close = tick.lastPrice bar.date = tick.date bar.time = tick.time bar.datetime = tick.datetime # K线的时间设为第一个Tick的时间 self.bar = bar # 这种写法为了减少一层访问，加快速度 self.barMinute = tickMinute # 更新当前的分钟 else: # 否则继续累加新的K线 bar = self.bar # 写法同样为了加快速度 bar.high = max(bar.high, tick.lastPrice) bar.low = min(bar.low, tick.lastPrice) bar.close = tick.lastPrice #---------------------------------------------------------------------- def onBar(self, bar): """收到Bar推送（必须由用户继承实现）""" # 撤销之前发出的尚未成交的委托（包括限价单和停止单） for orderID in self.orderList: self.cancelOrder(orderID) self.orderList = [] # 计算指标数值 self.barList.append(bar) if len(self.barList) <= 2: return else: self.barList.pop(0) lastBar = self.barList[-2] # 新的一天 if lastBar.datetime.date() != bar.datetime.date(): # 如果已经初始化 if self.dayHigh: self.range = self.dayHigh - self.dayLow self.longEntry = bar.open + self.k1 * self.range self.shortEntry = bar.open - self.k2 * self.range self.dayOpen = bar.open self.dayHigh = bar.high self.dayLow = bar.low self.longEntered = False self.shortEntered = False else: self.dayHigh = max(self.dayHigh, bar.high) self.dayLow = min(self.dayLow, bar.low) # 尚未到收盘 if not self.range: return if bar.datetime.time() < self.exitTime: if self.pos == 0: if bar.close > self.dayOpen: if not self.longEntered: vtOrderID = self.buy(self.longEntry, self.fixedSize, stop=True) self.orderList.append(vtOrderID) else: if not self.shortEntered: vtOrderID = self.short(self.shortEntry, self.fixedSize, stop=True) self.orderList.append(vtOrderID) # 持有多头仓位 elif self.pos > 0: self.longEntered = True # 多头止损单 vtOrderID = self.sell(self.shortEntry, self.fixedSize, stop=True) self.orderList.append(vtOrderID) # 空头开仓单 if not self.shortEntered: vtOrderID = self.short(self.shortEntry, self.fixedSize, stop=True) self.orderList.append(vtOrderID) # 持有空头仓位 elif self.pos < 0: self.shortEntered = True # 空头止损单 vtOrderID = self.cover(self.longEntry, self.fixedSize, stop=True) self.orderList.append(vtOrderID) # 多头开仓单 if not self.longEntered: vtOrderID = self.buy(self.longEntry, self.fixedSize, stop=True) self.orderList.append(vtOrderID) # 收盘平仓 else: if self.pos > 0: vtOrderID = self.sell(bar.close * 0.99, abs(self.pos)) self.orderList.append(vtOrderID) elif self.pos < 0: vtOrderID = self.cover(bar.close * 1.01, abs(self.pos)) self.orderList.append(vtOrderID) # 发出状态更新事件 self.putEvent() #---------------------------------------------------------------------- def onOrder(self, order): """收到委托变化推送（必须由用户继承实现）""" pass #---------------------------------------------------------------------- def onTrade(self, trade): # 发出状态更新事件 self.putEvent() if __name__ == '__main__': # 提供直接双击回测的功能 # 导入PyQt4的包是为了保证matplotlib使用PyQt4而不是PySide，防止初始化出错 from ctaBacktesting import * from PyQt4 import QtCore, QtGui # 创建回测引擎 engine = BacktestingEngine() # 设置引擎的回测模式为K线 engine.setBacktestingMode(engine.BAR_MODE) # 设置回测用的数据起始日期 engine.setStartDate('20120101') # 设置产品相关参数 engine.setSlippage(0.2) # 股指1跳 engine.setRate(0.3/10000) # 万0.3 engine.setSize(300) # 股指合约大小 engine.setPriceTick(0.2) # 股指最小价格变动 # 设置使用的历史数据库 engine.setDatabase(MINUTE_DB_NAME, 'IF0000') # 在引擎中创建策略对象 engine.initStrategy(DualThrustStrategy, {}) # 开始跑回测 engine.runBacktesting() # 显示回测结果 engine.showBacktestingResult() ## 跑优化 #setting = OptimizationSetting() # 新建一个优化任务设置对象 #setting.setOptimizeTarget('capital') # 设置优化排序的目标是策略净盈利 #setting.addParameter('atrLength', 12, 20, 2) # 增加第一个优化参数atrLength，起始11，结束12，步进1 #setting.addParameter('atrMa', 20, 30, 5) # 增加第二个优化参数atrMa，起始20，结束30，步进1 #setting.addParameter('rsiLength', 5) # 增加一个固定数值的参数 ## 性能测试环境：I7-3770，主频3.4G, 8核心，内存16G，Windows 7 专业版 ## 测试时还跑着一堆其他的程序，性能仅供参考 #import time #start = time.time() ## 运行单进程优化函数，自动输出结果，耗时：359秒 #engine.runOptimization(AtrRsiStrategy, setting) ## 多进程优化，耗时：89秒 ##engine.runParallelOptimization(AtrRsiStrategy, setting) #print u'耗时：%s' %(time.time()-start)